Irregularities in railway tracks are a key factor influencing the safety of trains. In this paper, rail track is considered to consist of consecutive track maintenance units whose individual defect states can be quantified in terms of a track quality index. A Markov stochastic process approach is used to evaluate the deterioration of a maintenance unit. A hazard model is formulated using the heterogeneity of the maintenance units, and a matrix of the Markov transition probabilities is constructed. The parameters of the developed models are estimated via a maximum log-likelihood function. The prediction model is validated with track irregularity data measured using track geometry cars.

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In recent decades, construction project scheduling optimization has received extensive attention from the research community. However, the most commonly used scheduling approach, the critical path method, is often inapplicable to transportation-type linear projects. Recently, the linear scheduling method (LSM) has demonstrated many advantages for such projects and has become a popular research subject. As a relatively novel scheduling method, LSM requires further improvement, as there are restrictions associated with the scheduling/optimization of linear projects. By analyzing results from previous studies, we propose a unique three-element mode, a description method for LSM's logical relationships and constraints system. An LSM-based scheduling optimization model based on constraint satisfaction problems and constraint programming is then proposed that could be used in classical scheduling optimization problems with flexibility, practicability, and solution superiority. The proposed model is verified using three practical transportation construction projects. Verification under six optimization scenarios demonstrates the advantages of our approach.

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